Job Requirements
Requirements:
- Proficiency in GPU utilization for AI models deploy.
- Proven track record of successfully deploying machine learning models in production environments
- Familiarity with model deployment strategies and best practices.
- Excellent problem-solving skills and the ability to troubleshoot and fix issues related to machine learning models.
- Strong communication skills, including the ability to effectively collaborate with clients and internal teams.
- Leadership skills to guide and mentor junior members of the machine learning team.
- A passion for staying updated with the latest trends and advancements in the field of AI/ML.
Responsibilities:
- Lead the development of machine learning models from inception to deployment, covering the entire lifecycle.
- Engage with clients through conference calls to understand their requirements and translate them into actionable technical solutions.
- Validate and collect data from various sources, ensuring its quality and suitability for the intended models.
- Rapidly prototype and iterate on different machine learning models, considering multiple approaches to solving complex problems.
- Implement and code machine learning algorithms, leveraging your expertise in programming languages like Python.
- Deploy models to both development and production environments, ensuring seamless integration and optimal performance.
- Provide comprehensive support and troubleshooting for internal and external teams encountering issues with machine learning models.
- Provide guidance to the machine learning team regarding the selection of models and strategies for model tuning.
- Streamline and optimize the machine learning development process to enhance efficiency and collaboration within the team.
- Conduct research to push the boundaries of deep learning, striving to provide technical solutions to real-world challenges across various domains.
Qualifications and Skills
- Bachelor's or master's degree in computer science, Engineering, Mathematics, or related field.
- Strong programming skills in Python.
- Experience with AI frameworks such as PyTorch.
- Experience with natural language processing (NLP) algorithms and models GPT-3, BERT.
- Extensive experience with data science toolkits and ML libraries.
- Demonstrated expertise in machine learning techniques and algorithms.
